The present disclosure relates generally to the field of data processing, and more particularly to sharing crowd sourced graphical representations.
Structured information may be defined as information whose intended meaning is explicitly represented in the structure or format of the data. Unstructured information may be characterized as information whose meaning requires interpretation in order to approximate and extract the intended meaning. Examples include natural language documents, speech, audio, images, and video. In other words, unstructured data is any data residing unorganized outside a database.
Unstructured data can include text, audio, video, and/or graphics. Unstructured information is believed to represent one of the largest and fastest growing sources of information available. In some estimation, unstructured data represents 80% of all corporate information. High-value information in this huge amount of data may be difficult to discover. Unstructured information may not be in a format adapted to search techniques. Searching for information in unstructured sources may not always be practical. First, data must be analyzed to detect and locate items of interest. The results must then be structured to facilitate searchability. Charts are graphical representations of data, in which data is represented by symbols, such as bars in a bar chart, lines in a line chart, or slices in a pie chart.
It is known to have internet-based competitions, such as contests with rewards for contest winners, to determine which person has made the best data visualization (for example, chart, graph, etc.) to represent a given set of unstructured data. These competitions are generally judged by a relatively small group of human “experts” (as opposed to a large group of people without special qualifications). These competitions do not allow the competitors to see each other's entries during the time that the competition is open to new entries. It is believed that the reason for this access restriction is so that the people designing new data visualizations will not build on each others work (by learning from each other's mistakes, etc.).